Risk assessment of venous thromboembolism in head and neck cancer patients and its establishment of a prediction model.

IMPORTANCE: Venous thromboembolism (VTE) is closely relevant to head and neck cancer (HNC) prognosis, but little data exist on the risk prediction of VTE in patients with HNC. OBJECTIVE: To study the risk factors regarding VTE in HNC patients and construct a nomogram model for its prediction. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional retrospective study was implemented to comparatively analyze 220 HNC patients from January 2018 to December 2021. The Lasso algorithm was used to optimize the selection of variables. A nomogram model for predicting HNC-associated VTE was established using multivariate logistic regression analysis. Internal validation of the model was performed by bootstrap resampling (1000 times). Calibration plot and decision curve analysis (DCA) were applied to evaluate the calibration capability of the prediction model. MAIN OUTCOME AND MEASURE: The demographics, medical history, blood biochemical indicators, and modalities of treatment were included for analysis. RESULTS: The incidence of HNC-associated VTE was 2.8% (55/1967) in authors' affiliation. Five variables of risk factors, including surgery, radiochemotherapy, D-dimer, aspartate transaminase, and globulin, were screened and selected as predictors by Lasso algorithm. A prediction model that incorporated these independent predictors was developed and presented as the nomogram. The model showed good discrimination with a C-index of 0.972 (95% CI: 0.934-0.997), and had an area under the receiver operating characteristic curve value of 0.981 (p < 0.001, 95% CI: 0.964-0.998). The calibration curve displayed good agreement of the predicted probability with the actual observed probability for HNC-associated VTE. The DCA plot showed that the application of this nomogram was associated with net benefit gains in clinical practice. CONCLUSIONS AND RELEVANCE: The high-performance nomogram model developed in this study may help early diagnose the risk of VTE in HNC patients and to guide individualized decision-making on thromboprophylaxis.

Effects of osseous structure based on three-dimensional reconstructive imaging evaluation in the assessment of temporomandibular joint disc position.

OBJECTIVES: This pilot morphological study aimed to investigate the association between anterior disc displacement (ADD) and the status of the mandibular condyle and articular fossa. MATERIALS AND METHODS: Thirty-four patients were divided into a normal articular disc position group and an ADD with and without reduction group. Images reconstructed were used to determine multiple group comparisons of these three different types of disc position, and the diagnostic efficacy for the morphological parameters with significant group difference was analyzed to assess. RESULTS: The condylar volume (CV), condylar superficial area (CSA), superior joint space (SJS), and medial joint space (MJS) all exhibited obvious changes (P < 0.05). Additionally, they all had a reliable diagnostic accuracy in differentiating between normal disc position and ADD with an AUC value from 0.723 to 0.858. Among them, the CV, SJS, and MJS (P < 0.05) had a significantly positive impact on the groups by analysis of multivariate logistic ordinal regression model. CONCLUSIONS: The CV, CSA, SJS, and MJS are significantly associated with different disc displacement types. The condyle in ADD exhibited altered dimensions. These could be promising biometric markers for assessing ADD. CLINICAL RELEVANCE: The morphological changes of mandibular condyle and glenoid fossa were significantly influenced by the status of disc displacement, and condyles with disc displacement had three-dimensionally altered condylar dimensions, irrespective of age and sex.